An Empirical Study on Price Differentiation Based on System Fingerprints
Thomas Hupperich, Dennis Tatang, Nicolai Wilkop, Thorsten Holz

TL;DR
This study investigates whether online platforms use system fingerprinting to implement price differentiation, by developing an automated scanner that mimics various user system attributes to detect pricing disparities.
Contribution
The paper introduces an automated system fingerprint-based price scanner to empirically detect online price differentiation related to user system features.
Findings
Identified instances of price differences based on system attributes
Demonstrated the feasibility of detecting fingerprint-based price discrimination
Provided insights into how online prices vary with user system characteristics
Abstract
Price differentiation describes a marketing strategy to determine the price of goods on the basis of a potential customer's attributes like location, financial status, possessions, or behavior. Several cases of online price differentiation have been revealed in recent years. For example, different pricing based on a user's location was discovered for online office supply chain stores and there were indications that offers for hotel rooms are priced higher for Apple users compared to Windows users at certain online booking websites. One potential source for relevant distinctive features are \emph{system fingerprints}, i.\,e., a technique to recognize users' systems by identifying unique attributes such as the source IP address or system configuration. In this paper, we shed light on the ecosystem of pricing at online platforms and aim to detect if and how such platform providers make use…
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Taxonomy
TopicsMedia Influence and Politics · Digital Platforms and Economics · Peer-to-Peer Network Technologies
